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Exact(11)
Neither forward nor backward selection was performed.
Backward selection was performed, with significance level for staying at 0.1.
A secondary analysis using stepwise backward selection was performed to confirm these results.
A multiple logistic regression analysis (backward selection) was performed to identify predictors of GPE.
Backward selection was performed, with significance level for staying (Slstay) = 0.1.
Backward selection was performed, a priori including all variables for the likelihood ratio test.
Similar(49)
Multiple linear regression analyses (backward selection) were performed to identify predictors of change in outcome on NRS pain, MPI- subscale interference and BDI-II.
Univariable and multivariable linear regression analyses with a stepwise backward selection were performed in order to analyse the predictive value of the independent variables at baseline and progress in MS disability on the use of care.
Backward model selection was performed to select risk factors for the final model.
Multiple logistic regression (using automated backward variable selection) was performed including those clinical parameters that showed at least a trend towards significance in univariate analysis (cut-off p-value = 0.1) using SPSS 15.0.
Backward stepwise selection was performed.
More suggestions(11)
backward elimination was performed
backward analysis was performed
backward selection was fitted
backward selection was based
backward method was performed
backward selection was employed
backward translation was performed
backward selection was used
backward selection was done
backward stepwise was performed
backward selection was applied
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